1. Field of Invention
This invention pertains to apparatus and processes for three-dimensional image reconstruction from data acquired in a positron emission tomograph (PET). More particularly, this invention pertains to apparatus and methods based on a parallel/pipelined architecture for processing data acquired as the bed moves through the tomograph.
2. Description of the Related Art
In a positron emission tomograph (PET) imaging system, a patient is injected with a radioactively tagged substance that the body normally metabolizes in some fashion. The radioactive tag used is a positron-emitting isotope of either an element found in the substance or an element that is substituted for another element in the substance. For example, a widely used isotope is the positron-emitting isotope of fluorine, 18F. This isotope is substituted, through a chemical synthesis process, for hydrogen in complex compounds such as glucose-forming fluro-deoxyglucose (FDG). When FDG is injected into a patient, the body will attempt to use it in the same fashion as it would normal glucose. Thus, there will be higher concentrations of positron emitters in areas where glucose is metabolized at higher levels, such as the brain, muscle tissue (the heart), and tumors.
As the FDG or other radiopharmaceutical isotopes decay in the body, they discharge positively charged particles called positrons. Upon discharge, the positrons encounter electrons, and both are annihilated. As a result of each annihilation event, gamma rays are generated in the form of a pair of diametrically opposed photons approximately 180 degrees (angular) apart. By detecting these annihilation “event pairs” for a period of time, the isotope distribution in a cross section of the body can be reconstructed. These events are mapped within the patient's body, thus allowing for the quantitative measurement of metabolic, biochemical, and functional activity in living tissue. More specifically, PET images (often in conjunction with an assumed physiologic model) are used to evaluate a variety of physiologic parameters such as glucose metabolic rate, cerebral blood flow, tissue viability, oxygen metabolism, and in vivo brain neuron activity.
Mechanically, a PET scanner consists of a bed or gurney and a gantry, which is typically mounted inside an enclosure with a tunnel through the center, through which the bed traverses. The patient, who has been treated with a radiopharmaceutical, lies on the bed, which is then inserted into the tunnel formed by the gantry. Traditionally, PET scanners are comprised of one or more fixed rings of detectors, surrounding the patient on all sides. Some newer scanners use a partial ring of detectors and the ring revolves around the tunnel. The gantry contains the detectors and a portion of the processing equipment. Signals from the gantry are fed into a computer system where the data is then processed to produce images.
Detectors on the detector rings encircling the patient detect the gamma rays, one on either side of the patient, and the time at which they were detected. Therefore, when two detectors on opposite sides of the patient have detected gamma rays that occurred within some time window of each other, it is safe to assume that the positron-electron interaction occurred somewhere along the line connecting the two detectors. If the detectors that detected the pair of gamma rays are located on the same ring, the coincidence plane, which is a transaxial plane, is called a direct plane. If the detectors are located on different rings, the coincidence plane, which is an oblique plane, is called a cross plane.
By histogramming the detected occurrences based on these lines of response (LOR), a pattern that uniquely describes the distribution of radioactivity is formed. The array in which the histogram is formed is typically called a sinogram. An image of the isotope distribution can be formed from these sinograms using any number of techniques that have been described in the prior art. However, the image that is produced is inaccurate due to several factors. As the gamma rays pass through the patient's body (and other objects, such as the patient bed), they are attenuated and scattered. Additionally, each gamma ray detector has a different response. All of these factors produce either noise or artifacts. Methods for correcting these effects are described in the prior art.
Positron emission tomography is one of the medical imaging modalities for which the transition from two-dimensional to three-dimensional acquisition has been most successful. Following pioneering work in the 1980s, the development after 1989 of multi-ring scanners equipped with retractable septa has led to the present widespread utilization of volume PET-scanners. These scanners have an open, collimator-less cylindrical geometry, which allows the measurement of coincidences between all pairs of detectors on the cylindrical surface.
Data collected in the transaxial or direct plane and in the oblique planes is three-dimensional (3D) data. These 3D data approximate line integrals of the radioactive tracer distribution along LORs which are not restricted to lie within transaxial planes. This is in contrast with the two-dimensional (2D) data acquired when the scanner is operated in 2D mode, in which the data collected is limited to LORs in the transaxial planes. The transition from 2D acquisition to 3D acquisition leads to a significant improvement of the scanner sensitivity, due to the increased number of measured LORs and to the elimination of the detector's shadowing by the septa.
Usually, 3D PET data are reconstructed using a reprojection algorithm (3DRP), which is a 3D filtered-backprojection (FBP) method obtained by discretizing an analytical reconstruction formula. Owing to the considerable number of LORs measured in 3D mode, it is not surprising that the 3DRP algorithm is much more time consuming than the 2D slice-by-slice FBP used to reconstruct data acquired in 2D mode. A further reason for this increased complexity is that the reconstruction of the 3D image is not decomposed into the reconstruction of a set of independent slices. Other algorithms relying on exact analytical formulae have so far been unable to reduce reconstruction time by factors larger than 2 compared to the 3DRP algorithm. In contrast, significant improvements in the reconstruction speed have been achieved using various combinations of the three following approaches. The first one is the introduction of faster, but often expensive, hardware. The second approach uses a reduced sampling of the 3D data to decrease the number of LORs which must be backprojected. Reduced sampling is achieved by adding groups of adjacent LORs in such a way that the resulting loss of spatial resolution remains acceptable for a given type of study. Finally, the third approach to faster 3D reconstruction is the use of approximate algorithms based on axial rebinning. The Fourier rebinning (FORE) process is one such approximate algorithm. The FORE algorithm is described in “Exact and Approximate Rebinning Algorithms for 3D PET data,” M. Defrise, P. Kinahan, D. Townsend, C. Michel, M. Sibomana, and D. Newport, IEEE Transactions on Medical Imaging, pp. 145-58, 1997.
The advantages of using a continuous axial scanning motion are described in “Implementation of True Continuous Whole Body PET Scanning,” M. Dahlbom, J. Reed, and J. Young, IEEE 2000 Medical Imaging Conference. This paper describes performing a scan by moving the patient bed in small, discrete steps. True continuous movement of the patient bed is described in “Methods for Improving Image Quality in Whole Body PET Scanning,” M. Dahlbom, DC Yu, S. Cherry, A. Chatziioannou, and E. Hoffman, IEEE Transactions on Nucl. Sci., Vol. 39, No. 4, pp. 1079-83, 1992. This second paper describes scanning a continuously moving subject and storing the data in list mode, which is later sorted into sinograms for reconstruction.